The similarities among different acquisitions of the same ﬁngerprint have never been taken into account, so far, in the feature space designed to detect ﬁngerprint presentation attacks. Actually, the existence of such resemblances has only been shown in a recent work where the authors have been able to describe what they called the “user-speciﬁc effect”. We present in this paper a ﬁrst attempt to take advantage of this in order to improve the performance of a FPAD system. In particular, we conceived a binary code of three bits aimed to “detect” such effect. Coupled with a classiﬁer trained according to the standard protocol followed, for example, in the LivDet competition, this approach allowed us to get a better accuracy compared to that obtained with the “generic users” classiﬁer alone.
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|Titolo:||Fingerprint Presentation Attacks Detection based on the User-Speciﬁc Effect|
|Data di pubblicazione:||2017|
|Appare nelle tipologie:||04.01 - Contributo in atti di convegno|